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- % Generated by roxygen2: do not edit by hand
- % Please edit documentation in R/Boruta.R
- \docType{data}
- \name{srx}
- \alias{srx}
- \title{Small redundant XOR data}
- \format{A data frame with 8 predictors, 4 relevant: A, B, AoB, AnB and nA, as well as 3 irrelevant N1, N2 and N3, and decision attribute Y.}
- \source{
- \url{https://mbq.me/blog/relevance-and-redundancy}
- }
- \usage{
- srx
- }
- \description{
- A synthetic data set with 32 rows corresponding to all combinations of values of five logical features, A, B, N1, N2 and N3.
- The decision Y is equal to A xor B, hence N1--N3 are irrelevant attributes.
- The set also contains 3 additional features, A or B (AoB), A and B (AnB) and not A (nA), which provide a redundant, but still relevant way to reconstruct Y.
- }
- \details{
- This is set is an easy way to demonstrate the difference between all relevant feature selection methods, which should select all features except N1--N3, and minimal optimal ones, which will probably ignore most of them.
- }
- \keyword{datasets}
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